Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification

no code implementations • 25 Jul 2022 • Rakshith Subramanyam, Mark Heimann, Jayram Thathachar, Rushil Anirudh, Jayaraman J. Thiagarajan

Model agnostic meta-learning algorithms aim to infer priors from several observed tasks that can then be used to adapt to a new task with few examples.

Classification Few-Shot Learning